Experience Manager provides some basic search capabilities out of the box. In this talk, we'll explore an external search platform for implementing an Experience Manager powered, search-driven site. As an example, we will use Apache Solr as a reference implementation and describe best practices for indexing content, exposing non-Experience Manager content via search, delivering search-driven experiences, and deploying the solution in a production setting.

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A virtual developer conference for Adobe Experience
Manager
Gaston Gonzalez | Do you need an external search platform for AEM?

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About Me

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Agenda
3
1 | What’s the problem?
2 | How can an external search platform help?
3 | How do you get started?
4 | Demo
5 | Q&A

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What’s the problem?

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What’s the problem?
5
Sites are becoming
increasingly
dynamic
Not all content is in
AEM (or should be)
Enterprise
integration can be
difficult

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Where is your enterprise data?
Web site data is typically distributed in disparate
locations:
• Digital media services
• Analytics
• Ratings & reviews
• Social & collaboration
• Product data
• CMS content
• Digital assets
• Internal RDBMs
• Legacy Systems
• Cloud-based APIs

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The Voice of the Customer & Marketing

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Enterprise Data Integration & AEM
Approach Pro Con
Real-time integration • Eliminates content
synchronization
• Performance dependent on
weakest link
• Data merging not possible
• Multiple calls required for
aggregated data views
Load data into AEM • Improved rendering performance • Data duplication
• Content synchronization
• Clustering and/or replication
Hybrid approach • A balance of the above • A balance of the above

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How can an external
search platform help?

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Search Platform: Features
Search
Platform
Full Text Search
Text Analysis
Linguistics & NLP
Federated SearchAutosuggest
Geospatial Search
Rich Documents
Faceted Search
Multi Lingual
Search
Hit Highlighting
More Like ThisDid You Mean

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Search Platform: Use Cases
 Full Text Search
 Federated Search
 Dynamic Navigation
 Site Navigation
 Breadcrumbs
 List Pages
 Content Aggregation
 Landing Pages
 Product Pages
 Dynamic Content Pods
 Recommendations
 Carousels, Spotlights

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Federated Search
Search across all content types
Integration Approach
1. Normalize common fields across content
types.
2. Allocate a content type field for filtering and
boosting.
3. Load all content type documents into a single
collection.
4. Consider using the eDisMax query parser.
5. Consider layering on boost queries or
function queries to meet relevancy goals
(e.g., popularity, freshness, etc.)

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Dynamic Navigation – List Pages
Category pages such as product list pages
Integration Approach
1. Index category hierarchy information along with
your documents and encode path levels.
2. Implement navigation components using Solr’s
facet.prefix along with a wildcard query
(*:*).
3. Consider layering on boost queries or function
queries to meet relevancy goals (e.g., higher
margin products, popularity, freshness, etc.)
https://wiki.apache.org/solr/HierarchicalFaceting

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Content Aggregation (1 of 2)
Entertainment Industry
• Shows
• Series
• Episodes
• Images
• Videos
Integration Approach
1. Establish a well-defined tag taxonomy.
2. Tag related, disparate content types with tags.
3. Implement components to query across tags.
4. Consider layering on boost queries or function queries
to meet relevancy goals (e.g., popularity, freshness,
etc.)

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Content Aggregation (2 of 2)
Life Sciences Industry
• Product data
• Material Safety & Data Sheets (MSDS)
• Certificates of Analysis (COA)
• FAQs

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Item-based Recommendations
More Like This performs document
similarity based on term vectors.
Integration Approach
1. Leverage the More Like This request handler*
and/or search component*.
2. Identify fields that capture the “aboutness” of
the item and enable term vectors.
3. Issue a field query using the document ID for
which you want related documents.
4. Consider layering on boost queries or function
queries to meet relevancy goals (e.g.,
popularity, freshness, etc.)
5. Consider using copy fields and filtering out
“noisy” tokens.
https://cwiki.apache.org/confluence/display/solr/MoreLikeThis

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Full Text Search in AEM
Integration Approach Pros Cons
Jackrabbit Oak • OOTB
• JCR based model
• Can be used with the custom approach
(i.e. shared Solr: oak collection + custom
collections)
• JCR property-based model
• Does not map well to UI view
• Limited search features*
External Search Platform (custom integration) • Leverage existing investment
• Full search API support
• Indexing
• Search
• Full control over document model
• Full control of ranking/scoring
• Scale Solr independently for AEM
• Implementation effort
• Additional infrastructure needed

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How do you get
started?

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Getting Started with Solr
Infrastructure Sizing
• Document corpus
• Document size
• Index & search latency
• Query volume…
Deployment Mode
• SolrCloud
• Standalone
• Master / Slave
Analysis
• Content Inventory
• Requirements
• Data Modeling
• Signal Modeling…
Solr Implementation
• Collections
• Schema Definition
• Query Definition
• Scoring Functions…
AEM Integration
• Indexing
• Search
• Presentation
Other Data Store
Integration
• Indexing
Assumptions & Recommendations
• Apache Solr as a shared search platform
• Each content source controls its
own indexing.
• AEM “owns the glass” and provides
the user experience.
• Leverage SolrJ directly.
• Considering finding Solr-specific
resources for search-specific
development.

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AEM Solr Search: A Reference Implementation
 Open source reference integration between Apache Solr and AEM
 Rapidly prototype front-end, search-driven experiences
 Rich set of extendable UI components (results, facets, pagination, etc.)
 Sample search site – Geometrixx Media Sample
 SolrJ OSGi bundle
 Quickstart distributions
 Solr 4.x – Maven sub project
 Solr 5.x – Vagrant + VirtualBox
 SolrCloud, Standalone, Master/Slave support
http://www.aemsolrsearch.com/

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AEM Indexing Approaches
Approach Details AEM Solr Search Notes
Event Driven (Direct) 1. Event Listener
2. Adapter/Sling Model
3. SolrJ API
Yes • Triggered on content
add/update/delete
Event Driven (Indirect) 1. Event Listener
2. Adapter/Sling Model
3. Send to ETL
No. Indexing interface in next
release.
• Triggered on content
add/update/delete
On-Demand (Direct) 1. Adapter/Sling Model
2. Walk JCR
3. SolrJ API
No. Future release. • Triggered by user or scheduler
Poor Man's Polling (Direct) 1. Content serialization Servlet
2. External shell script
3. Post to Solr’s Update
Request Handler
Yes • Only recommended for small
sites
• Triggered by user or scheduler
ETL Polling (In Direct) 1. Connect to data source
2. Transform, merge, enrich,…
3. Index Solr
Yes. AEM Solr Search: Product
Demo
• Approach covered in demo
• Triggered by user or scheduler
http://www.slideshare.net/therealgaston/adapt-to2014-integratingopensourcesearchwithaemfinalr2

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AEM + Product + Solr
Architecture

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AEM + Product + Solr Demo
 Data Sources
 AEM Geometrixx Media Site
 Best Buy Movie Product Data
 Platforms
 AEM 6.1
 Apache Solr 5.4.1 (SolrCloud)
 Apache Camel 2.17
 Application Code
 AEM Solr Search
 AEM Solr Search – Product Demo

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Apache Camel as an ETL (Best Buy -> Solr)
http://www.gastongonzalez.com/tech-blog?tag=Apache+Camel

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AEM Solr Search: Product Demo

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Demo

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Reference Architecture

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Multi-Collection in SolrCloud Mode

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Multi-Core in Master/Slave Mode

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Resources
 Sample Code
 AEM Solr Search: http://www.aemsolrsearch.com
 AEM Solr Search: Product Sample: https://github.com/GastonGonzalez/aem-solr-search-
product-sample
 Related Talks
 CIRCUIT 2016 - Advanced AEM Search - Consuming External Content and Enriching Content
with Apache Camel
 adaptTo() 2014 - Integrating Open Source with AEM:
http://www.slideshare.net/therealgaston/adapt-to2014-
integratingopensourcesearchwithaemfinalr2
 Blogs
 My tech blog: http://www.gastongonzalez.com

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Q&A
32
Gaston Gonzalez
aemsolr@headwire.com
Twitter: @therealgaston
Blog: www.gastongonzalez.com

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